In the field of digital wireless communication, packet communication represented by Internet communication and speech storage, speech signal coding and decoding techniques are essential for effective use of channel capacity and storage media for radio waves. In particular, a CELP (Code Excited Linear Prediction) speech coding and decoding technique is a mainstream technique
A CELP speech coding apparatus encodes input speech based on pre-stored speech models. To be more specific, the CELP speech coding apparatus separates a digital speech signal into frames of regular time intervals, for example, frames of approximately 10 to 20 ms, performs a linear prediction analysis of a speech signal on a per frame basis, finds the linear prediction coefficients (“LPC's”) and linear prediction residual vector, and encodes the linear prediction coefficients and linear prediction residual vector separately. As a method of encoding linear prediction coefficients, it is general to convert linear prediction coefficients into LSP parameters and encode these LSP parameters. Also, as a method of encoding LSP parameters, vector quantization is often performed for LSP parameters. Here, vector quantization is a method for selecting the most similar code vector to the quantization target vector from a codebook having a plurality of representative vectors (i.e. code vectors), and outputting the index (code) assigned to the selected code vector as a quantization result. In vector quantization, the codebook size is determined based on the amount of information that is available. For example, when vector quantization is performed using an amount of information of 8 bits, a codebook can be formed using 256 (=28) types of code vectors.
Also, to reduce the amount of information and the amount of calculations in vector quantization, various techniques such as multi-stage vector quantization (MSVQ) and split vector quantization (SVQ) are used (see Non-Patent Document 1). Here, multi-stage vector quantization is a method of performing vector quantization of a vector once and further performing vector quantization of the quantization error, and split vector quantization is a method of quantizing a plurality of split vectors acquired by splitting a vector.
Also, there is a technique of performing vector quantization suitable for LSP features and further improving LSP coding performance, by adequately switching the codebooks to use for vector quantization based on speech features that are correlated with the LSP's of the quantization target (e.g. information about the voiced characteristic, unvoiced characteristic and mode of speech). For example, in scalable coding, by utilizing the correlation between wideband LSP's (which are LSP's found from wideband signals) and narrowband LSP's (which are LSP's found from narrowband signals), classifying the narrowband LSP's by their features and switching codebooks in the first stage of multi-stage vector quantization based on the types of features of narrowband LSP's (hereinafter abbreviated to “types of narrowband LSP's”), wideband LSP's are subjected to vector quantization (see Patent Document 1).
Non-Patent Document 1: Allen Gersho, Robert M. Gray, translated by Yoshii and other three people, “Vector Quantization and Information Compression,” Corona Publishing Co., Ltd, 10 Nov. 1998, pages 524 to 531
Patent Document 1: International publication No. 2006/030865 pamphlet